In techniques for modeling geological reservoirs, conditionality is a primary requirement of reservoir models. Not only should reservoir models honor statistics of property distributions and spatial heterogeneity, but also the local direct (e.g., well cores and logs, etc.) and indirect (e.g., seismic information, provenance, allogenic cycles, etc.) conditioning data. Without conditionality, reservoir models do not provide accurate predictions of reservoir response. In addition, due to the vast model space of potential heterogeneity results, it is not practical to expect coincidental model and conditioning data match.